2020 state of enterprise machine learning
Algorithmia has talked with thousands of people in various stages of machine learning (ML) maturity and in various roles connected to ML. Following the report we published last year , we conducted a two-prong survey this year, polling nearly 750 people across all industries from companies actively engaged in building ML lifecycles to those just beginning their ML journeys.
We analyzed the responses from both survey groups for insight into their work, their companies’ ML roadmaps, and the changes they’ve seen in recent months concerning ML development. Our 2020 State of Enterprise ML report includes the findings of that effort as well as our analysis of the results.
Below we have shared eight questions that were posed in our survey and the results associated with each question so you can explore the data, conduct your own analysis, and see how your company compares to others like it.
After you explore the data, download the 2020 State of Enterprise ML report to read our analysis and see where we think ML development is headed.
Which title best describes your position at your organization?
Which industry do you currently work in?
How many data scientists does your company employ?
This was a write-in question, and answers ranged from 0-4,000 data scientists.
49% of survey respondents answered 1-10 data scientists
How many individuals are employed by your organization worldwide?
What percentage of your data scientists' time is spent deploying ML models?
36% of survey participants said their data scientists spend a quarter of their time deploying ML models
36% of survey participants said their data scientists spend a quarter to half of their time deploying ML models
20% of survey participants said their data scientists spend half to three-quarters of their time deploying ML models
7% of survey participants said their data scientists spend more than three-quarters of their time deploying ML models
36% of survey respondents said their data scientists spend a quarter of their time deploying ML models
On average, how long does it take your organization to put a trained model into scaled production?
What are all the ways you use AI and ML models in your organization today?
Reducing costs246 survey respondents
Improving the customer experience226 survey respondents
Generating customer insights and intelligence220 survey respondents
Increasing customer satisfaction189 survey respondents
Retaining customers189 survey respondents
Detecting fraud184 survey respondents
- Reducing costs 246 survey respondents
- Improving the customer experience 226 survey respondents
- Generating customer insights and intelligence 220 survey respondents
- Increasing customer satisfaction 189 survey respondents
- Retaining customers 189 survey respondents
- Detecting fraud 184 survey respondents
Which stage of AI/ML adoption are you currently at in your organization?
Download the 2020 State of Enterprise ML report to see our analysis and where we think ML development is headed.
Algorithmia is committed to making our 2020 State of Enterprise Machine Learning report data freely available as part of our vision to empower every organization to achieve its full potential through the use of artificial intelligence and machine learning.
To learn more about Algorithmia and how we deliver the last-mile solution for model deployment, visit our product page .